Algorithm to minimize iterative computation in a process for the analysis or design of a physical system

ABSTRACT

A process is described for the solution of a system of algebraic equations. A general purpose computer is programmed to perform the steps of the process. These steps include (1) forming a consolidated matrix descriptive of the entire system of equations and variables, (2) identifying design (specified) variables and/or iterative variables by a unique elimination procedure so as to minimize the number of iterative variables and to minimize the number of relations which must be solved simultaneously (i.e. minimize nested iterative calculations), (3) using a calculation procedure to determine the computational sequence for solution of the equations, and (4) solving these equations in the order determined by the computational sequence and determining the numerical values of the system variables. This process reduces computer computation time and identifies those essential variables which must be specified (design variables) in order to obtain a solution. Any physical system which is described by an under-specified or adequately specified set of equations can be solved by this process. One application involves designing a chemical processing plant by solving an under-specified set of equations descriptive of the units, streams, etc. of the plant.

United States Patent Ramirez, Jr. et al. I

[54] ALGORITHM TO MINIMIZE ITERATIVE COMPUTATION IN A PROCESS FOR THE ANALYSIS OR DESIGN OF A PHYSICAL SYSTEM [72] Inventors: W. Fred Ramirez, Jr., Boulder;

Charles R. Vestal, Denver, both of Colo.

[73] Assignee: Marathon Oil Company, Findlay,

' Ohio [22] Filed: Oct. 9, 1970 [2'11 Appl. No.: 79,579

Lee and Rudd, On The Ordering of Recycle Calculations Aiche Journal, November 1966, pp. 1184- [is] 3,702,003 [451 0ct.31, 1972 Primary Examiner-Joseph F. Ruggiero Attorney-Joseph C. Herring, Richard C. Willson, Jr. and Jack L. Hummel [5 7] ABSTRACT A process is described for the solution of a system of algebraic equations. A general purpose computer is programmed to perform the steps of the process. These steps include (1) forming a consolidated matrix descriptive of the entire system of equations 'and variables, (2) identifying design (specified) variables and/or iterative variables by a unique elimination procedure so as to minimize the number of iterative variables and to minimize the number of relations which must be solved simultaneously (i.e. minimize nested iterative calculations), (3) using a calculation procedure to determine the computational sequence for solution of the equations, and (4) solving these equations in the orderdetermined by the computational sequence and determining the numerical values of the system variables.

This process reduces computer computation time and identifies those essential variables which must be specified (design variables) in order to obtain a' solution. Any physical system which is described by an under-specified, or adequately specified set of equations can be solved by this process. One application involves designing a chemical processing plant by solving an under-specified set of equations descriptive of the units, streams, etc. of the plant.

9 Claims, 7 Drawing Figures Variables With. Zero Frequency Are Eliminated.These Are Known Variables Compute Variable Frequency Check It All Eauations Have Been Eliminated From The Plont Structural Matrix YES Print Variables which Have Not Been Eliminated. These Are Design Variables And/Or iterative Variables Associated with Any Hierarchy.

Eliminate Minimum Frequency Minus One Equations,Each Of which Must Have An Entry Frequency.

in The Variable Of Minimum increment Hierarchy By One Level.

Print How Many Iteralive Variables Detected And The Hierarchy Level.

Variables Which Have Fre quency =1 Are Eliminated. lt Their Respective Equo tions Have Not Previously Been Eliminated,They Are Now Also Eliminated.An Equation Can Only Be Eliminated Once.

mJIb i Print The Variables And The Hierarchy Level For Variables Whose Equations Hove These Are Design Variables And/Or Iterative Variables Associated With Any Hierarchy Level Less Than or Equal To The Present Levelv Been Previously Eliminated.

Terminate Elimination procedure in determine des/yn and item/ire var/ables.

PATENTEDHMI i912 3.702003 SHEETl 0F 7 Set Hierarchy To Zero IlI v I Variable Frequency is Computed 1 a? y Y 111 t a Variables With Zero Frequency Are Eliminated.Th ese Are Known Variables Check it All Equations Have Been Eliminated From The.

Plant Structural Matrix I lb 7 Print Variables Which Have Not Been Eliminated; These Are Design Variables And/Or Iterative Variables Associated Yes IZI Ia With Any Hierarchy.

Eliminate Minimum Frequency Variables Which Have Fre- Minus One Equations,Each Of quency =1 Are Eliminated.

Which Must Have An Entry If eir Respective Equa- In The Variable Of Minimum Hons Hflve Not Previously Frequency Been Eliminated,They Are Now Also Eliminated.An Term'nuie ma Equation Can Only Be Increment Hierarchy By Eliminated Once' Been Previously Eliminated. These Are Design Variables And/Or Iterative Variables Associated With Any Hier- I E/l'ml'flflflbn procedure In archy Level Less Than Or determine design and Equal To The Present Level. ire/alive var/ables. Flgr I W/T/VESSES v INVENTORS 4 .w. F. RAMlREZ,JR.

I ,e c. R. VESTAL PATENiEflnmum 3.702.003

' SHEET 2 or 7 Set Hierarchy Level To Maximum Level Detected In Elimination Procedure (Fig.1)

II I Set Design Variable Columns To Zero I Check if All Variables Have Been Eliminated Calculate Equation And Variable Freuencies Check if Minimum Equation Fre uenc is 1 Eliminate E uqtions with F Decrease The Hierarchy Level it All Essential Iterative quency a The Variable Variables In The Previous Hierarchy Have Been Solved For- Contributing That Frequency -SDI o Temporarily Set All Iterative Variables In This I Hierarchy To Zero Terminate l Calculate The "Equation And Variable Frequencies I Check If Equation Frequency ls Zero ya Ia l I Ib 'For Equations With Frequency =1,E|iminate For one Hermlve That Equation And The Variable Contributing VOFlOble in Terms of To That Frequency Providing That The Others Variable Frequency is 1 IXI heck lf Equations Eliminated EqualTh Number Of Essential lterativevariables in This Hierarchy No Yes Reset iterative Variable Locations Except in Those Equations Which Have Been Eliminated Check If Variable Frequency is Zero And Variable Has Not Been Eliminated IXIII Indicate That lgplicit Iteration Has een Procedure for deIermm/ng Defected campuM/iana/ sequence.

W/TT/VESSES MIVEIVTORS I X; r a w. F. RAMIREZ, JR. WW Q ZUL e c. R. VESTAL PATENTEDucm m2 3.702.003

sum 3 or 7 MIXER 7 HEAT EXCHANGER Fig.

WITNESS$ ,nv vE/vrms f/Z w. E RAMIREZ, JR.

9M1, a k/4M" vESTAL PATENTEnnmal I972 3.702.003

SHEET 7 0F 7 DISTILLATE OVERHEADSV PARTIAL CONDENSER TRAY REFLUX FEED:

TRAY 2 TRAY 3 REBOILER Fig. 5

-w/r/vs$s I INVENTORS 1 w. E RAMIREZ, JR.

0 C. R. VESTAL ATT 'NEY CROSS REFERENCES TO RELATED APPLICATIONS No related U. S. Patent applications are known to the inventors.

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to the field of computational equipment, computational processes and computer'programs particularly useful for the sequencing of the solution of individual equations within a set of simultaneous equations so as to minimize computational time. Some or all of the equations may be nonlinear in character. The system of equations is further characterized by the fact that it is either adequately specified or under-specified, with the number of variables appearing in the system greater than or equal to the number. of equations, i.e., the degrees of freedom of the system is greater than, orequal to, zero. To solve an under-specified system, certain design variables must be specified to reduce the degrees of freedom of the system to zero.

2. Description of the Prior Art In chemical process design, a process flow diagram must be initially defined. The design engineer is then faced with the task of determining a computational strategy in order to perform process and equipment calculations. In the past, this strategy has been determined from experience and engineering intuition. The

work of Rudd, (see The Synthesis of Systems Designs: 1, Elementary Decomposition Theory, AICHE Journal, Vol. 14,No. 2, pp 343, March 1968) is one of the earliest attempts to place this decision on some mathematical basis. The process of the present invention is an extension and improvement of Rudds work and is based on the objective of minimizing the number of relations which must be solved simultaneously. For non-linear algebraic equations this affords a minimization of iterative computation.

Lee and Rudd, On the Ordering of Recycle Calculations, AICHE Journal, Vol. 12, No. 6, pp 1 184, November 1966, teach a method of determining whether design and/or iterative variables are present in a system of equations. However, they do not provide insight for distinguishing iterative from design variables. In contrast, the present invention identifies those variables which must be design variables and furthermore provides insight into choosing iterative variables. The invention specifies which choices are available in choosing iterative variables.

In describing a plant process, design variables can be process can handle either explicit or implicit iteration in solving for the iterative variables.

SUMMARY General Statement of the Invention Given a set of algebraic equations, some or ,all of which may be non-linea.r, containing more variables (unknowns) than equations, and descriptive of some physical system, the process of the present invention selects which of the variables should be specified in order to minimize the iterative calculation necessary to obtain a solution. The present invention also involves equipment, processes, and computer programs for selecting the order in which individual equations within a set of simultaneous algebraic equations are to be solved so as to minimize the total time and total calculational effort necessary to the solution of the entire set of equations.

Utility of the Invention Calculational machines, particularly general purpose digital computers, and the processes and computer programs taught herein, are useful in the solving of sets of underspecifiedsimultaneous algebraic equations so as to minimize the expense and effort involved. Such sets of equations are often encountered in daily commercial and scientific operations, e.g., in cost analysis, chemical engineering plant design, electronic circuit design, distribution analysis, etc. The cost of solution of such equations is very substantial and methods for reducing the computer time involved and thus the cost therefor, are highly desirable and have widespread utility.

BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 is a block diagram depicting the elimination procedure for determining the design anditerative variables according to the present invention.

FIG. 2 is a block diagram depicting the procedure for determining the computational sequence in solving these sets of equations according to the present invention.

FIG. 3 is a block diagram depicting a portion of a chemical processing plant which will be used in Example V to show how thisprocess design will be solved according to the present invention.

FIG. 4 is a block diagram depicting an electronic circuit which will be used in Example VI to show how this electronic design will be solved according to the present invention.

FIG. 5 is a block diagram depicting a distillation tower which will be used in Example VII to show how this process design will be solved according to the present invention.

FIG. 3a is a diagram depicting the system structural matrix for Example V which will be solved according to the present invention.

FIG. 4a is a block diagram depicting the system structural matrix for Example VII which will be solved according to the present invention.

Two actual programs written in Algol computer language are included in appendix A to this specification. The first of these is entitled Elimination and implements the preferred embodiment shown in FIG. 1. The second program is entitled Calculational Sequence and implements the preferred embodiment shown in FIG. 2. These programs are illustrative rather than limitative of the invention.

DESCRIPTION OF THE PREFERRED EMBODIMENTS l. The following terms are defined to facilitate the reading and understanding of the specification and claims of the present invention.

By iterative calculation is meant a method of successively approximating the solution to an equation using a recursion formula until the equation is satisfied within a prescribed degree of accuracy.

By matrix is meant a rectangular array of numbers, or other elements, useful as a computational device.

By structural matrix is meant a matrix which designates which variables are known in each equation of a set of equations and which variables are unknown in each such equation. The structural matrix is formed by letting each row represent an equation and each column represent a single variable. At each intersection of a row and column a designator is inserted to show whether that variable is known or unknown in that equation. For example, a 1 may be used to indicate that that variable is unknown in that equation and a 0. to indicate that that variable is known in that equation. Obviously, rows and columns may be interchanged so that variables are designated by rows and equations designated by columns.

By known variable is meant that, in the equation in question and at the point in the calculation in question, the variable has a determined numerical value or that the variable does not appear in the equation.

' By unknown variable is meant that, in the equation in question and at the point in the calculation in question, the variable does not have a determined numerical value and the variable does appear in the equation.

By consolidating matrices is meant combining a plurality of matrices to form a single matrix by adding the rows of one matrix onto a base matrix and providing additional columns as necessary to provide one column for each variable contained in the combined matrix.

By system structural matrix is meant the matrix formed by consolidating all of the structural matrices which describe a given system.

By design variable is meant an initially unknown variable which is given a numerical value at an intermediate point in the computational process and thus becomes a known variable. In any set of equations the number of design variables will be equal to the number of degrees of freedom of the system structural matrix.

By iterative variable is meant an unknown variable, the numerical value of which will be assumed so that its true numerical value can be iteratively calculated.

By frequency of occurrence of a variable, or variable frequency is meant the number of equations which contain that variable as an unknown.

By computational sequence is meant the order in which the numerical values of unknown variables is determined and the sequence also indicates in which equation the numerical value of each variable is to be determined.

By hierarchy level" is meant the occurrence of a minimum variable frequency greater than one. The detection of such a hierarchy level indicates the presence of one or more iterative variables. The first hierarchy level detected is designated a value of l, and each succeeding hierarchy level value is incremented by one.

By nested iterative calculations is meant iterative calculation which must be performed within other iterative calculation(s).

By redesignating is meant changing the value of an unknown variable designator to indicate that the variable is known, e.g., redesignating l (unknown) to 0 (known).

By explicit is meant solving an equation for an unknown variable directly in terms of other known variables.

By implicit is meant solving for an unknown variable by means of a defining relation which is not itself solved for the unknown variable.

2. Basic Process Steps The invention utilizes either a special purpose computing machine (computer) or a general purpose computer programmed to perform, in sequence, the following steps as applied to a set of algebraic equations, some or all of which can be non-linear, which contain more variables than equations:

a. One or more structural matrices is formed in which each row is an equation of the system and in which each column is a variable of the system, or vice versa, and wherein each variable is designated as being either known or unknown;

b. The structural matrices are then consolidated, as necessary, to form a single system structural matrix descriptive of the entire system;

0. Design and/or iterative variables are identified by algebraic operations on the system structural matrix so as to minimize the number of iterative variables, and identifying iterative variable hierarchy level(s) so as to minimize nested iterative calculations;

d. Once the design and/or iterative variables are identified, the computational sequence is specified for solving the system of equations by algebraic manipulation of the system structural matrix;

e. The equations are then solved in the order selected by the computational sequence, thereby determining values for the system variables.

3. Identifying Design and/or Iterative Variables by an Elimination Procedure The algebraic operations defining the procedure are depicted in FIG. 1, and reference should be made to this drawing in the following description of the procedure. The parenthetical references below refer to the blocks of that figure.

The purpose of the elimination procedure is to determine which variables must be specified (design variables) in order to minimize the number of iterative variables needed to solve the set of algebraic equations. It is also the purpose of the elimination procedure to identify different levels of iterative calculations (hierarchy levels) which can be used in the following procedure to determine the calculational sequence so as to minimize the number of nested iterativecalculations.

Initially, the hierarchy level is set to zero (I) and the frequency of occurrence of each variable of the plant structural matrix is computed (II). Since some of the variables of the system structural matrix may be known variables, these variables will occur with zero frequency and these variables are eliminated (III). The effect is to reduce the number of columns in the matrix.

A check is made to see if all of the equations have been eliminated from the plant structural matrix (IV). If this is the case, the entire algebraic operations of the algorithm are completed and variables which have not been eliminated in the procedure are design and/or iterative variables associated with any hierarchy level (Vb). The equations should then be solved according to the procedure for determining the computational sequence (see VI, 4 herein). If all the equations havent been eliminated, the variable frequency is again computed, and the algorithm continues (Va)..

Those variables which appear in the plant structural matrix with a frequency of one (VI) can be solved for directly and are therefore designated as known and eliminated from the matrix with-their respective equations, i.e., the column (variable) is made zero and the respective row (equation) is also made zero (VIIb). The algorithm proceeds by systematically searching for and eliminating variables of frequency one.

If the minimum variable frequency is greater than one'(VI), this implies that iteration is necessary and that a hierarchy level has been detected. The number of iterative variables to be detected (and hence the number of equations to be eliminated) necessary to continue the solution is the minimum variable frequency minus one (VIIa). For instance, if the minimum variable frequency is three, three minus one, or two equations having an entry in the variable of minimum frequency must be eliminated. Once the minimum frequency minus one iterative variables have been detected, within any given hierarchy level, the hierarchy level is incremented by one (VIIIa). As FIG. 1 indicates, the algorithm proceeds by going back to check to see if all the equations have been eliminated from the plant structural matrix, and the process is repeated (i.e., go to A in FIG. 1).

- The detection of iterative and/or design variables is as follows. Variables whose equations are subsequently eliminated (so that the variable frequency becomes zero) are denoted as either design or iterative variables. The relative order of appearance of these variables With the detection of iterative loops (hierarchy level) is important, for it tells whether they are essential to a particular iterative loop. A variable can only be associated with a hierarchy level lower than or equal to the one in which it was detected. Those variables associated with the zero hierarchy level are design variables only, and thus are immediately specified.

If in any given hierarchy level, more than the minimum frequency minus one design or iterative variables are detected, the engineer chooses which of these variables should be specified (design variables) with the remaining variables (minimum frequency minus one in number) denoted as essential iterative variables associated with that particular hierarchy level. In some instances, no design or iterative variables will be found within a given hierarchy level. The iterative variable(s) associated with that hierarchy level is then detected within a subsequent hierarchy level. This situation represents a nested loopa loop within another loop. The present algorithm and invention tends to minimize the number of these loops within loops and thus minimizes the number of nested iterative calculations required during the computational sequence procedure (discussed below under VI, 4).

As the design and recycle variables are detected, they may be printed or otherwise identified (IXa, VIIIb). The number -of degrees of freedom of the system will be equal to the number of design variables which must be specified.

4. Procedure for the Determining Computational Sequence An information flow diagram for the computational sequence procedure is given in FIG. 2 of the drawings, and the parenthetical references below are to the blocks of that figure.

The computational sequence procedure is essentially a preferred method of sequencing and solving the equations of the structural matrix utilizing the design and iterative variables found in the elimination procedure and the order in which the iterative variables were detected. The computational sequence preferably proceeds in the reverse order of hierarchy as determined in the elimination procedure, i.e., setting hierarchy equal to the maximum, then reducing it in steps of one (I). l

The computational sequence starts by assuming knowledge of the design variables (II). This information is implemented by replacing all onesby zeroes in the system structural matrix, for instance. The next step is to calculate the equation and variable frequencies (IV). Those equations which have a frequency equal to one can be solved uniquely for the unknown variable (V). These equations with frequency one are eliminated along with the variable contributing to that frequency (Vla). The algorithm continues in this fashion as long as possible, eliminating from the system structural matrix the equations of frequency one and their associated variables.

When the minimum equation frequency is greater than one (V), iterative information is required and the iterative variables in the present hierarchy are temporarily assumed (i.e. set to zero) in order to continue the computational procedure (VII). The hierarchy level is decreased by one when all essential iterative variables in the previous hierarchy have been solved for (VIb).

After the iterative variables of the present hierarchy level are set to zero, the equation and variable frequencies are then recalculated (VIII). A check is then made to see if the equation frequency is zero (IX). If not, the equations of frequency one (and which contain at least one of the iterative variables assumed in the present hierarchy) are eliminated (redesignated as known) and the variable contributing to that frequency is also eliminated, provided that the variable frequency is greater than one (Xa). If the equation frequency checked is zero, one iterative variable is solved in terms of the other(s) (Xb).

Next, a check is made to see if the number of equations eliminated (redesignated as known) is equal to the number of essential iterative variables in the hierarchy level under consideration (X). If this is not ing the frequency of occurrence of each variable and by computing the number of unknown variables remaining in each equation and proceeding with a check to see if the minimum equation frequency is one. This procedure is continued until all the system variables have been redesignated as known. If during this process, the frequency of occurrence of an iterative variable goes to zero without the iterative variable having been redesignated as known, then an implicit iterative loop has been found (III).

Detection of an iterative loop for each hierarchy level defined a set of equations containing the iterative variable(s) under consideration and which must be solved simultaneously by iterative techniques. What essentially takes place is that in one equation the iterative variable is assumed to be known and designated a value. Theiterative loop is then traced through to other equation(s) until the iterative variable is again encountered. At this point, the iterative variable is redesignated as unknown and that equation is solved explicitly for the iterative variable. If the value obtained is equal to or within a prescribed incremental tolerance of the assumed value originally given the iterative variable the computational sequence procedes by descending to the next hierarchy level. If the calculated value of the iterative variable is not within the incremental tolerance of the assumed value, iteration continues until convergence to the answer. A preferred convergence technique is taught in Wegstein, .l.l-I., Accelerating Convergence of Iterative Processes,

Comm. ACM, Vol. 1, No. 6, pg 9 (1958), although any iterative and convergence technique may be employed and be within the scope of the invention. An implicit iterative loop is essentially the same, except that the tolerance check for closure of the loop is made on a variable other than the iterative variable.

As the equations are solved by the particular computational sequence provided herein, the values for the system variables are determined.

EXAMPLES these examples and the final results of the algorithm rather than the individual details of each algorithm will be reported.

EXAMPLE I (Simplified Example of the Invention) Given a system described by the following set of algebraic equations,

the algebraic operations defining the elimination procedure to be used to identify the design and/or iterative variables are depicted in FIG. 1. Reference should be made to this figure in order to better understand the following description. Parenthetical references refer to the blocks of FIG. 1.

From the set of three equations and three unknown variables, form the system structural matrix. For convenience, a 1 will designate an unknown variable in an equation and a 0 will designate a known variable. Each equation will form one row of the system structural matrix and each variable will form one column. The system structural matrix is shown below:

l jg, 0

Variable Frequency 2 l 2 III. No variables appear with zero frequency; therefore, none are originally known.

IV. All equations have not been eliminated from the system structural matrix; therefore, continue.

VI. Test whether the minimum variable frequency equals1.

Vllb. Variables which have frequency equal to 1 are eliminated. If their respective equations have not previously been eliminated, they are now also eliminated. An equation can only be eliminated once. Therefore, in our example problem, variable x and equation f will be eliminated. The resulting structural matrix is shown below. For convenience, the elimination process will be presented in the structural matrix by redesignating as known the variable and equation which are eliminated. Here, the variable and equation which are eliminated will also be enclosed in brackets to further indicate the fact that they have been eliminated. In actual computer operation, this elimination is accomplished by setting a true-false (Boolean) variable equal to true when elimination is properly to be done.

this operationwould appear as shown below:

it, l zl 3 [I11 0 0 1 o 0 [fit] It can be seen from this plant structural matrix that variable x;, was eliminated along with equation f IV. Test whether all of the equations have been eliminated. Va. Since one equation remains, the variable frequency is once again computed.

x, x x Variable Frequency l O 0 VI. Test whether the minimum variable frequency is equal to 1 Variable x, has a frequency of 1" occurring in equation f VIIb. Variables which have frequency equal to l are eliminated'along with their respective equation, if it has not previously been eliminated.

' l ll l al l a] lf-l 0 0 0 0 0 O I U11] 0 0 0 IV. Test whether all of the equations have been eliminated from the system structural matrix.

Vb. Since all of the equations have been eliminated, variables which have not been eliminated are now printed. These are the design and/or iterative variables associated with the hierarchy level as detected. For this example problem, there are no design or iterative variables and the hierarchy level remains at 0.

At thispoint, the purpose of the elimination procedure has been fulfilled; that is, the variables which must be specified (design variables) in order to reduce the degrees of freedom of the system of equations to zero have been determined. Additionally, the different levels of iterative calculations (hierarchy levels) have also been determined. For this simplified example problem. there are no design variables since the initial degrees of freedom of the system was zero and, further, there are no iterative variables detected and the hierarchy level remains at O.

The process of this invention now continues by determining the computational sequence. FIG. 2 of the drawings depicts the information flow diagram for the computational sequence. Parenthetical references below are to blocks of FIG. 2 and reference should be made to these blocks to better understand the description that follows. The algebraic manipulations to be followed in determining the computational sequence are based on results obtained in determining the design and/or iterative variables following the algebraic operations depicted on FIG. 1. Both algebraic procedures are similar in that each start from the original system structural matrix.

a l O l Following FIG. 2 a general purpose digital computer is programmed to perform the following sequential operations: e

I. Set hierarchy level to the maximum level detected in the elimination procedure (FIG. 1); in this case this will be set to O. This again means that there will be no iterative variables associated with this problem.

II. Set design variable columns to 0. In this example problem there are no design variables, so no columns will be changed.

III. Test whether all variables have been eliminated from the system structural matrix. All variables have not been eliminated; therefore, continue.

IV. Calculate equation and variable frequencies.

, f1 f 2 fa Equation Frequency 2 2 .r, x, x Variable Frequency 2 l 2 1] 2 3 f, o o 1 [f2] 0 0 0 o 1 1 III. Continue the procedure by checking to see if all variables have been eliminated. Since only one of the original three variables has been eliminated, we continue.

IV. Calculate equation and variable frequencies.

f1 f2 Equation Frequency l U 2 1 X2 X3 Variable Frequency 0 l 2 V. Test whether the minimum equation frequency is equal to 1. The frequency of occurrence of unknown variables in equation f is now equal to l since the information about whether or not it is known or unknown for variables x has been calculated in the previous step using equation f Vla. We will therefore eliminate equations with frequency equal to l and the variable contributing that frequency.

IXII X2 I uI Ill 0 0 [f2] 0 0 0 .lll 0 0 III. Continue by checking to see if all variables have been eliminated. Since one variable remains, continue. IV. Calculate equation and variable frequencies.

. It f: -fa Equation Frequency 0 0 1 Variable Frequency O l 0 V. Test whether the minimum equation frequency is equal to 1. The frequency of occurrence of unknown variables in equation f; is now equal to 1 because the knowledge of the value for variable x;, has been determined from equation f in the previous step.

Vla. Eliminate equations with frequency equal to one and the variable contributing that frequency.

II 2] 1] [fl] 0 0 0 O O 0 [fit] 0 0 0 f3, to solve for variable x At this point, all three unknown variables have been solved for.

The calculational sequence may further be conveniently shown in the following table:

Sequence No. Equation Variable Hierarchy Level I f, x, 0 2 .fl x3 0 3 f x 0 In executing this algorithm, the variable frequencies were calculated at each step but were not used; Variable frequencies will only be used in the case of iterative calculations.

EXAMPLE II (Example of the Invention) Given a system described by the following set of algebraic equations f3( 2 3) 0 the algebraic operations depicted in FIG. 1 which define the elimination procedure will be referenced in a manner similar to that followed in Example I.

Form the system structural matrix from the set of three equations and four unknown variables. As in Example I, a 1 will designate an unknown variable in an equation and a 0 will designate a known variable. Each equation will form one row of the system structural matrix and each variable will form one column. The system structural matrix is shown below:

i 1 l f5, 0

Following FIG. 1, a general purpose digital computer is programmed to perform the following sequential operations:

I. Set hierarchy level to zero.

II. Calculate variable frequency of occurrence.

Variable Frequency x, x x,

III. No variables appear with an initial frequency of 0; therefore, none are originally known.

IV. All of the equations have not been eliminated from the system structural matrix; therefore, continue.

VI. Test whether the minimum variable frequency equals 1.

VIIb Variables which have frequency equal to l are eliminated. If their respective equations have not previously been eliminated, they are now also eliminated. An equation can only be eliminated once. During this elimination procedure, the process will be represented in the system structural matrix by redesignating as known the variable and equation which are eliminated (i.e., insert all 0 s). The variable and equation which are eliminated will further be enclosed in braces to indicate the fact that they have been eliminated. In our example problem, variable x and equation f and variable x and equation f will be eliminated.

Variable Frequency a VI. Test whether the minimum variable frequency is equaltol.," VIIb. Variables which have frequency equal to l areeliminated. If the respective equation has not previously been eliminated, it is now also eliminated. An equation can only be eliminated once. In this example problem, variable x, and equation f meet these criteria. The resulting system structural matrix after this elimination would appear as shown below.

. VI. Test whether all of the equations have been eliminated. Vb. Since all of the equations have been eliminated, variables which have not been eliminated are now designated as design and/or iterative variables associated with the hierarchy level as detected. For this example problem, the variable x has not been eliminated. Therefore, it is either a design or an iterative variable. However, the hierarchy level has not been incremented and remains at therefore, variable x; must be a design variable associated with this problem. The results of the elimination procedure may be conveniently represented in the following table.

Hierarchy Variables Not Number Eliminated Interpretation 0 w x Design Variable The elimination procedure has just terminated by determining which variable must be specified (design variable) in order to reduce the degrees of freedom of the system of equations to 0. Additionally, the elimination procedure has detected that iterative calculations will not be required for the solution of this problem. For this example problem, there is one design variable, no iterative variables, and the hierarchy level remains at A computational sequence must now be determined using the process of FIG.- 2. This process will also use the results obtained in determining the design and/or iterative variables following the algebraic operations in FIG. 1. Starting from the original system structural matrix,

1 2 3 4 f 1 0 l l f 1 0 0 0 f, O l l 0 following the steps of FIG. 2, a general purpose digital computer is programmed to perform the following sequential operations:

I. Set the hierarchy level to the maximum level detected in the elimination procedure (FIG. 1) which, in this case, will be set to 0. This again means that there will be no iterative variables associated with this problem.

II. Set the design variable columns to O. For this example problem, all of the entries in the column variable x will be set to 0." The resulting structural matrix is shown below:

x X; n] 4 f l 0 O I f: l 0 0 0 fa 0 l O 0 Design variables will be further indicated by enclosing them in brackets so that we will know they have been eliminated from the system structural matrix.

III. Test whether all of the variables have been eliminated from the system structural matrix. Since only one variable has been eliminated, the algorithm will continue.

IV. Calculate equation and variable frequencies.

l f2- a Equation Frequency 1 x, x x x Variable Frequency 2 l 0 l V. Test whether the minimum equation frequency is equal to l.

VIa. Equations which have frequency equal to I and the variable which contributes that frequency are now eliminated. In this example problem, equation f and variable x,, and equation 13 and variable x will be eliminated. As before, the elimination procedure will be indicated by bracketing the equation and variable and by redesignating as known that equation and variable in the system structural matrix.

i] [X2] [I t, f, 0 0 0 1 U3] 0 0 0 o [A] 0 0 0 0 III. Test whether all of the variables have been eliminated. Since variable x, remains, the algorithm continues.

IV. Calculate equation and variable frequencies.

Equation Frequency fl 2 fa l 0 0 Variable Frequency x, 1 x x,

[X1] [X2] [X3] [X4] U1] 0 0 0 o [/21 0 0 o 0 m 0 o o 0 III. Test whether all variables have been eliminated. Since all of the variables have now been eliminated, the algorithm terminates.

The calculational sequence has just been determined for this example problem. Variable x would be solved for using equation f in the first step. In the second step,

.Scquence No.

may be used to conveniently show the calculational sequence' Equation Variable Hierarchy Level hbb In determining this calculational sequence, variable frequencies were calculated but were not used. Variable frequencies will be used only in the case of iterative calculations.

It should be noted that in executing the procedure to determine the calculational sequence, we have conveniently eliminated equations with frequency of I in a left to right order. The algorithm will work equally as wellif equations are eliminated from right to left or in a random sequence.

EXAMPLE Ill (Example of the Invention) Given a system described by the following set of algebraic equations the algebraic operations depicted in FIG. 1 will be used to determine the design and/or iterative variables for this system.

The system structural matrix representative of this system is shown below: I

Following FIG. 1, a general purpose digital computer is programmed to perform the following sequential operations:

I. Set hierarchy level to 0.

II. Calculate variable frequency of occurrence.

.r, X: Variable Frequency III. Test whether any variables initially appear with frequency. In our example problem, no variables appear with a frequency equal to 0; therefore, none are originally known.

IV. Test whether all equations have been eliminated from the plant structural matrix. Since no equations have been eliminated, we continue the process.

VI. Test whether the minimum variable frequency is equal to l.

Vla. In this example problem, no variable appears with a frequency equal to 1. Therefore, we must eliminate minimum frequency minus one equations, each of these equations having an entry in the variable of minimum frequency column. In our example problem, the minimum frequency is equal to 2; therefore, 2--l or 1 equation must be eliminated. Taking variable x we can see that equation f has an entry in the column of minimum frequency. We will, therefore, eliminate equation f,. This elimination is shown in the system structural matrix shown below.

f. j}, O

It should be noted in this example problem that either equation f or equation )3 could also have been eliminated since they have entries in columns which have the minimum frequency of occurrence. However, for convenience, the algorithm proceeds through the system structural matrix from top to bottom and from left to right.

VIIIa. Increment the hierarchy by one level. The

hierarchy level is now equal to 1 IX. At this point denote that one iterative variable (number of iterative variables is equal to the minimum frequency minus 1 equations) has been detected, and the hierarchy level is equal to l IV. Test whether all equations have been eliminated from the plant structural matrix. Since two equations have not been eliminated, we continue the process.

Va. Compute the variable frequency.

Variable Frequency 1 1] 2 lul [fr] 0 o 0 [f 0 l 0 Us] 0 0 0 This system structural matrix shows the results of eliminating variable x, and equation f and variable x and equation )3.

IV. Test whether all equations have been eliminated from the plant structural matrix.

Vb. All of the equations have now been eliminated, print the variables which have not been eliminated. These are design variables and/or iterative variables associated with any hierarchy level detected in the problem. For this example problem, there are no design variables (degrees of freedom equal zero), and one iterative variable has been detected along with a hierarchy level equal to 1. Further, the iterative variable is variable x since it was not eliminated from the plant structural matrix. Results of this elimination procedure shown in the following table.

l x, Iterative Variable We continue now by determining the computational sequence. Following FIG. 2, a general purpose digital computer is programmed to perform the following sequential operations starting from the original system structural matrix.

X f. 1 f. 1 f. g

l. Set hierarchy level to the maximum level detected in the elimination procedure (FIG. 1). For this example problem, this will be set to l This means that there will be one iterative level associated with this problem. Since the iterative level is equal to l there will be no possibility of nested iterations; that is, iterations within other iterations.

II. Set design variable columns to O. For this example problem, there are no design variable, so no columns will be changed.

III. Test"whether all variables have been eliminated from the system structural matrix. Since we have not eliminated any variables, we will continue.

IV. Calculate equation and variable frequencies;

Equation Frequency V. Test whether the minimum equation frequency is equalto 1. Since the minimum frequency is equal to 2, we must continue the algorithm.

Vlb. Decrease the hierarchy level if all essential iterative variables in the previous hierarchy level have been solved for. Since this is not the case, we again continue.

VII. Temporarily set all iterative variables in this hierarchy to 0." For this example problem, this involves temporarily assuming that the value of variable x is known. This, again, is conveniently shown in the following system structural matrix. A temporarily assumed variable will be indicated by enclosing the variable in parentheses rather than in brackets which have been used to show that the variable has been eliminated.

2) f1 I f:

fir

VIII. Calculate the equation and variable frequen- Variable Frequency 0 IX. Test whether any equation frequencies have been reduced to 0. Since none have been reduced to O continue.

Xa. For equations with frequency equal to 1,

eliminate that equation and the variable contributing to that frequency providing that the variable frequency is greater than 1. For this example problem, the equation frequency of equation f is equal to 1 and the variable contributing to that frequency, variable x has a variable frequency equal to 2. Therefore, this is a valid elimination step.

[*1] 2) 3 f1 0 0 l [[2] 0 0 0 j}, 0 O l XIII. Test whether any variable frequency has been reduced to O and the variable has not been eliminated. Since this is not the case, continue.

III. Test whether all variables have been eliminated.

Since two variables remain, proceed.

IV. Calculate equation and variable frequencies.

f fl f3 Equation Frequency 1 ll 2 Variable Frequency 0 l 2 V. Test whether the minimum equation frequency is equal tol.

VI. Eliminate equations with frequency equal to 1 and the variable contributing that frequency. In this case, equation f together with variable x;, will be eliminated.

1] 2 1] U1] 0 0 0 U2] 0 0 0 O l 0 III. Test whether all variables have been eliminated. Variable x has not been eliminated; therefore, continue. 7

IV. Calculate equation and variable frequencies.

. fa Equation Frequency 0 O V. Test whether the minimum equation frequency is equal to 1. Variable x appears in equation f and the minimum equation frequency is equal to [f2] 0 o o lfal 0 0 0 III. Test whether all variables have been eliminated.

Since this is now the case, the algorithm has terminated.

The calculational sequence for this example problem involving an iterative variable has just been determined. The computational sequence would proceed by assuming the value of the variable x and using this value in equation f, to calculate the value of the variable x,. In the second step, the value of variable x, would be used in equation f to solve for the unknown variable x In the third step, the value just calculated for the variable x would be used in equation f to calculate a value of variable x The computational sequence as described will continue until the value of the variable x which is calculated from equation f;, in the third step would be within some prescribed tolerance of the value of variable x which was assumed initially to be used in the first step of the calculational procedure in equation 2 to calculate variable x It should be further noted that the type of iteration which has been detected here is explicit; that is a value for the variable x will be assumed and the resulting value of variable x will be calculated directly.

In the case of iterative calculations, the representation of the calculational sequence in a table is very convenient. The table depicting the calculational sequence for this problem is shown below.

Sequence No. Equation Variable Hierarchy Level Assume Variable f: XI fl fir Loop to Sequence 1 EXAMPLE IV (Example of the Invention) Following the process of FIG. 1, a general purpose digital computer is programmed to perform the following sequential operations:

I. Set hierarchy level to 0.

II. Calculate variable frequency of occurrence.

Variable Frequency x, x, x, x,

III. Test whether any variables initially appear with 0 frequency. None are originally known.

IV. No equations have been eliminated from the system structural matrix. Therefore, continue.

VI. Test whether the minimum variable frequency is equal to 1. For this example problem, the minimum variable frequency is not equal to l it is equal to 2 and occurs in both variable x, and in variable x VIIa. Eliminate the minimum frequency minus one equations, each of which must have an entry in the variable of minimum frequency. Therefore, we could eliminate either equation f or f since each of these equations have entries in variable x,, or we could eliminate equations f, or f since each of these equations has an entry in variable x For convenience, we will eliminate equation f,. The resulting system structural matrix would appear below.

VIIIa. The hierarchy level is now incremented by 1.

It is now set equal to l IX. The number of iterative variables detected in the hierarchy level will now be denoted. One iterative variable will be listed as being detected since the minimum frequency minus one was equal to one, and the hierarchy level will be printed as being equal to one.

IV. Test whether all equations have been eliminated from the plant structural matrix. Since only one has been eliminated, we continue.

Va. Compute the variable frequency.

.X 1 X Variable Frequency 1 2 3 3 VI. Test whether the minimum variable frequency is equal to 1.

VIII). Variables which have frequency equal to l are eliminated. If their respective equations have not previously been eliminated, they are now also eliminated. An equation can only be eliminated once. In this example problem, equation f and variable x, will be eliminated. The resulting system structural matrix after this operation would appear as shown below.

- IV. Test whether all equations have been eliminated from the plant structural matrix. Since three equations remain, continue. Va. Compute the variable frequency.

Variable Frequency x, x, x x,

VI. Test whether the minimum variable frequency is equal to I. .This is-the case for variable x in equation];

. Vllb. Variables which have frequency equal to l areeliminated. If their respective equations have not previously been eliminated they are also eliminated. An equation can only be eliminated l5 7 once. The resulting system structural matrix is shown below.

[fr] 0 0 0 0 0 -[f,] 0 O 0 0 0 [fr] 0 0 0 O 0 f, 0 0 .I 1 l j; 0 0 O l I IV. Test whether all equations have been eliminated.

Since two equations remain, continue. Va. Compute variable frequency.

Variable Frequency VI. Test whether the minimum variable frequency is equal to 1.

' Vllb. Variables which have frequency equal to l are eliminated. Since their respective equations have not previously been eliminated, they are now also eliminated. An equation can only be eliminated once. Therefore, in this operation variable x and equation f will be eliminated first. When variable x is attempted to be eliminated, this cannot happen because the equation has just been eliminated in the previous step. Obviously, we could have taken equation f}, and variable x and then not been able to eliminate variable x.,; however, for convenience, we have proceeded in an orderly left to right manner through the system structural matrix. The resulting system structural matrix is shown below.

i] [I2] ha] [*4] X5 [fr] 0 o 0 0 0 U2] 0 0 0 0 o Lfal 0 0 0 0 0 m o o o 0 0 [fa] 0 0 0 o 0' VIIIb. Print the variableand the hierarchy level for those variables with frequency equal to l whose equations have been previously eliminated. These are design variables and/or iterative variables associated with any hierarchy level less than or equal to the present level. In this case, we will print that variable x is an iterative variable associated with hierarchy level l IV. Test whether all equations have been eliminated from the plant structural matrix. Since all of the equations have now been eliminated, the algorithm will terminate. Results of the elimination process for this example problem are shown in the following table.

Hierarchy Variables Not Number Eliminated Interpretation 0 None Iterative Variable Variable x the only variable which was not eliminated, has been shown to be the iterative variable necessary to solve this problem.

The process of this invention will now continue by determining the computational sequence. The algebraic procedure to do this must start from the original system structural matrix.

Following FIG. 2, a general purpose digital computer is programmed to perform the following sequential operations:

I. Set hierarchy level-to the maximum level detected in the elimination procedure (FIG. 1). In this case, this will be hierarchy level equal to I." This means that there will be one iterative level associated with this problem.

II. Set design variable columns to O. For this example problem, there are no design variables; therefore, no columns will be changed.

III. Test whether all variables have been eliminated from the system structural matrix. Since we have not eliminated any variables, the algorithm will continue.

IV. Calculate the equation and variable frequencies.

Equation Frequency i Variable Frequency 2 3 3 3 2 V. Test whether the minimum equation frequency is equal to l The minimum equation frequency in this case is equal to 2, appearing both in equation f and in equation 1",.

Vlb. Decrease the hierarchy level of all essential 5 iterative variables in the previous hierarchy level have been solved for. Since this is not the case, continue.

VII. Temporarily set all iterative variables in this hierarchy to 0. This results in the following system structural matrix. As before, a temporarily assumed variable will be enclosed in parentheses.

IX. Test whether the equation frequency is 0. This is not the case; therefore, we will continue.

Xa. For equations with frequency equal to l, we

will eliminate that equation and the variable contributing to that frequency, provided that the variable frequency is greater than l In this example problem, the equation frequency of equation f -,is equal to l, and variable x which is the variable that contributes that frequency, has a frequency of occurrence equal to 3. The resulting system structural matrix, after this elimination, is shown below.

1 3 4] f, 1 1 0 0 f, 1 1 1 0 0 f, 0 1 1 0 0 j; 0 0 1 0 0 [/3] 0 0 0 0 0 XI. Test whether the number of equations eliminated is equal to the number of essential iterative variables in this hierarchy. The number of essential iterative variables is equal to 1, and one equation has been eliminated.

XII. Reset iterative variable locations except in those equations which have been eliminated. The system structural matrix now appears as follows.

1 's 4] 5 1; l l O 0 O f, l l l 0 O f, 0 l l 0 0 j; 0 0 l O l [fd 0 O O O 0 XIII. Test whether any variable frequency is 0 and the variable has not been eliminated. Since this does not occur, continue.

III. Test whether all variables have been eliminated.

Since four variables remain, continue.

IV. Calculate equation and variable frequencies.

f f f Equation Frequency 2 3 2 2 I x x. I Variable Frequency 2' a 3' o 1* V. Test whether the minimum equation frequency is equal to 1. Since the minimum equation frequency is equal to 2, we continue.

Vlb. Decrease the hierarchy level if all essential iterative variables in the previous hierarchy have T been solved for. This is not the case because 1:, has

not been solved for; therefore, continue, still working in hierarchy level l VH. Temporarily set all iterative variables in this hierarchy to 0. The resulting system structural matrix is shown below.

1 [a] (an) f, 1 1 0 0 0 f: 1 1 1 0 o f, 0 1 1 0 0 f 0 0 l 0 0 [fa] 0 0 0 0 0 VIII. Calculate the equation and variable frequencies.

I Equation Frequency 2 g a I 8 I X X 1 Variable Frequency IX. Test whether the equation frequency is 0 for any equation which has not been eliminated.

Xa. For equations with frequency equal to 1 eliminate that equation and the variable contributing to that frequency, providing the variable frequency is greater than 1. The equation frequency of equation f, is equal to I, and the variable contributing to that frequency is variable x which has a frequency of occurrence equal to 3.We will therefore eliminate equation f, and variable x;,. The resulting system structural matrix is shown below.

1 3] 4] (*3) f; l l 0 0 0 f, l l 0 O O f; 0 l 0 O 0 [f 0 0 0 0 0 [f 0 0 O 0 0 X1. Test whether the number of equations eliminated equal the number of essential iterative variables in this hierarchy. Since this is the case, continue.

XII. Reset the iterative variable locations except in those equations which have been eliminated. The resulting system structural matrix is 1 2 4] *3 f, l l O O O f, l l 0 0 O f; O l O O 0 [LI 0 0 0 0 0 [f5] 0 0 0 O 0 XIII. Test whether any variable frequency is 0" and that variable has not been eliminated. At this point it can be seen that the frequency of occurrence of variable x, has been reduced to 0, and that variable has not been eliminated. 

1. In a process for the analysis or design of a physical system, which system is represented by algebraic equations, some or all of which may be non-linear, with a minimum of iterative calculation, by solving said equations in the order selected by a computational sequence and thereby determining numerical values for variables in said algebraic equations, the improvement comprising in combination determining said computational sequence by use of a programmed computing system having stored in its internal memory a program enabling the computing machine to perform in combination the steps of: a. forming a single system structural matrix in which each row is an equation of said system and each column is a variable of said system, or vice-versa, and wherein each variable is designated in each equation as being either known or unknown, b. identifying design and/or iterative variables by algebraic operations on the system structural matrix so as to minimize the number of said iterative variables, and identifying iterative variable hierarchy levels, when present so as to minimize nested iterative calculations, c. selecting the computational sequence for solution of said equations, said sequence being selected by algebraic manipulation of the system structural matrix.
 2. The process of claim 1 wherein the algebraic operations which minimize the number of iterative variables comprise in combination: a. computing the frequency of occurrence of each variable in the system structural matrix, b. eliminating variables with zero frequency of occurrence from the system structural matrix, said zero frequency variables being already known, the number of variables in said system structural matrix being thereby reduced, c. computing the number of unknown variables remaining in each equation, d. if unknown variables still remain, recomputing the frequency of occurrence of each variable, e. determining the minimum frequency of occurrence of unknown variables and then redesignating as known, equations which contain the minimum frequency variables until the number of equations redesignated as known equals the minimum frequency of occurrence minus one, f. recomputing the frequency of occurrence of each unknown variable and indicating that minimum frequency minus one iterative variables have been identified as being within the remaining unknown variables, indicating that a hierarchy level has been detected, g. redesignating as known any unknown variable which appears in only one equation after step d. and also redesignating the equation as known, provided that said equation has not been previously designated as known, h. designating as ''''design or iterative variables'''' each unknown variable which appears in only one equation after step d. said equation having been redesignated as known in accordance with step g. above, said ''''design or iterative'''' variables associated with any hierarchy level designated by a number less than or equal to the number designating the present hierarchy level.
 3. The process of claim 1 wherein the algebraic manipulations for selecting the computational sequence for solution of said equations so as to minimize nested iterative calculations comprises in combination the steps of: a. selecting a set of design variables and designating them as known, b. determining the frequency of occurrence of unknown variables and, also, computing the number of unknown variables in each equation of the system structural matrix, c. redesignating as known those variables which appear by themselves in an equation and redesignating as known that equation; but if it is determined that the minimum number of unknown variables remaining in each equation is greater than one, then, d. proceeding by temporarily designating as known all iterative variables appearing in the hierarchy level under consideration, e. redesignating as known, an unknown variable with a frequency of occurrence greater than one and simultaneously redesignating as known an equation in which the only unknown variable is that unknown variable which equation also contains at least one iterative variable, f. checking to see if the number of unknown variables in each equation of the system structural matrix is equal to zero and if the number is equal to zero solving for one iterative variable in terms of the other(s), g. checking to see if the number of equations redesignated as known is equal to the number of essential iterative variables in the hierarchy level under consideration, and if the number is less than the number of essential iterative variables, proceeding in accordance with step d., above, h. redesignating as unknown those iterative variables within the iterative variable hierarchy under study, which have not been redesignated as known in accordance with step d. above, i. if all system variables have been redesignated as known, designating as the calculational sequence, the order in which the system variable and the corresponding equation have been redesignated as known, j. if unknown variables still remain, recomputing the frequency of occurrence of each variable and by computing the number of unknown variables remaining in each equation and proceeding in accordance with step c. above.
 4. The process of claim 2 wherein the algebraic manipulations for selecting the computational sequence for solution of said equations comprises in combination the steps of; a. selecting a set of design variables and designating them as known, b. determining the frequency of occurrence of unknown variables and, also, computing the number of unknown variables in each equation of the system structural matrix, c. redesignating as known those variables which appear by themselves in an equation and redesignating as known that equation; but if it is determined that the number of unknown variables remaining in each equation is greater than one, then, d. proceeding by temporarily designating as known all iterative variables appearing in the hierarchy level under consideration, e. redesignating as known an unknown variable with a frequency of occurrence greater than one and simultaneously redesignating as known an equation in which the only unknown variable is that unknown variable which equation also contains at least one iterative variable, f. checking to see if the number of unknown variables in each equation of the system structural matrix is equal to zero and if the number is equal to zero solving for one iterative variable in terms of the other(s), g. checking to see if the number of equations redesignated as known is equal to the number of essential iterative variables in the hierarchy level under consideration, and if the number is less than the number of essential iterative variables, proceeding in accordance with step d., above, h. redesignating as unknown those iterative variables within the hierarchy under study, which have not been redesignated as known in accordance with step d. above, i. if all system variables have been redesignated as known, designating as the calculational sequence, the order in which the system variable and the corresponding equation have been redesignated as known, j. if unknown variables still remain, recomputing the frequency of occurrence of each variable and by computing the number of unknown variables remaining in each equation and proceeding in accordance with step c. above.
 5. The process of claim 1 wherein the algebraic operations which minimize the number of iterative variables comprise in combination: a. computing the frequency of occurrence of each variable in the system structural matrix, b. eliminating variables with zero frequency of occurrence from the system structural matrix, said zero frequency variables being already known, the number of variables in said system structural matrix being thereby reduced, c. computing the number of unknown variables remaining in each equation, d. if unknown variables still remain, recomputing the frequency of occurrence of each variable, e. determining the minimum frequency of occurrence of unknown variables and then redesignating as known, equations which contain the minimum frequency variables until the number of equations redesignated as known equals the minimum frequency of occurrence minus one, f. recomputing the frequency of occurrence of each unknown variable and indicating that minimum frequency minus one iterative variables have been identified as being within the remaining unknown variables, indicating that a hierarchy level has been detected, g. redesignating as known any unknown variable which appears in only one equation after step d. and also redesignating the equation as known, provided that saiD equation has not been previously designated as known, h. designating as ''''design or iterative variables'''' each unknown variable whose variable frequency becomes zero after step d. and whose equations have been redesignated as known in accordance with step g. above, said ''''design or iterative'''' variables associated with any hierarchy level designated by a number less than or equal to the number designating the present hierarchy level.
 6. A process according to claim 1 wherein said structural matrix is descriptive of a system in the cost analysis art.
 7. A process according to claim 1 wherein said structural matrix is descriptive of a system in the plant design art.
 8. A process according to claim 1 wherein said structural matrix is descriptive of a system in the electronics art.
 9. A process according to claim 1 wherein said structural matrix is descriptive of a system in the distribution analysis art. 